In cellular communications systems, a demodulator is used at a receiver to extract data symbols such as 1-bits and 0-bits that are modulating a communications signal.
The function of a demodulator is complicated by the addition of additive white Gaussian noise (AWGN) and co-channel interference (CCI) to the information signal as it is transmitted through the flat-fading mobile-radio environment. AWGN is introduced because of long-term fading effects, which attenuate the strength of a signal as the distance it travels increases, and short-term fading effects, which are caused by time dispersive media and local reflections. CCI is introduced when several communication channels in geographically close proximity to one another, using the same or closely spaced frequencies, begin to interfere with each other. It is a goal of the art to design cost-effective and rapid demodulators that extract modulating symbols from communications signals, notwithstanding the addition of noise and interference to the signals as they travel through the mobile radio environment.
The nature of the problem can be elucidated if the communications signal arriving at the input of a demodulator is analysed. More specifically, if one considers chopping up the signal along its time-axis into a plurality of segments that each correspond to one or a small number of symbols, such a segment, hereinafter the received signal, can be expressed in the following form: EQU r(n)=s(n)+.alpha.v(n)
The variable "n" is an index used to delineate the different received signals that comprise the communications signal received from the transmitter. "s(n)", hereinafter the information signal, is the part of the received signal that was modulated by one or more data symbols at the transmitter. Once the demodulator has determined the information signal, it can easily demodulate symbols from it. ".alpha." is a fading coefficient used to model the Doppler effect and is normally assumed to have a constant value over short-periods of time, the duration of the periods being a function of the mobile speed. "v(n)" is the part of the received signal caused by the combined effects of AWGN and CCI, hereinafter the interference signal. The problem can thus be described as isolating the information signal from within the received signal, given that both the information signal and the interference signal are unknown.
The solution to the problem is made easier because, assuming a digital modulation scheme is in use, a demodulator always has partial knowledge of the information signal. This knowledge is that the information signal can only be one of x.sup.N possible signals, where x is the number of symbols modulating each information signal, and N is the number of symbols supported by the modulation scheme in use. For example, if a .pi./4-DQPSK modulation scheme is in use, the information signal carrying a single symbol would have the following form: EQU s(n)=s(n-1)e.sup.jnB/4,
where B=1,3,5 or 7
In this example, the information signal would have to be one of only four possible signals.
This narrowing of the solution set for the information signal, is important because it allows demodulators to take advantage of cross-correlation detection techniques. These techniques are centered around a method of detecting signals in which the received signal is compared, point to point, with a reference signal that is an estimate of what the received signal should be if modulated by a given symbol. The output of such a detector is a measure of the degree of similarity between the received signal and the reference signal. Demodulators can take advantage of these techniques, by setting the reference signals of a cross-correlation detector to equal each of the x.sup.N possible information signals that could be within the received signal, and then selecting the reference signal that most closely correlates with the received signal as an estimate of the information signal.
More work must be done however, before relying on such cross-correlation detection techniques to correctly identify information signals within received signals. This is because differences between a reference signal and a received signal could be just as easily attributable to the effects of CCI and AWGN, as to differences between the underlying modulating symbols of the signals. Two signals that seem well-correlated may in fact only seem that way due to CCI and/or AWGN effects. Likewise, two signals that are in fact modulated by the same symbol may be poorly correlated with each other due to CCI and/or AWGN effects.
Therefore, in order to function in an environment that is heavily affected by CCI and/or AWGN, it is desirable that demodulators that use cross-correlation detection techniques, hereinafter referred to as correlation demodulators, be able to distinguish between differences between received and reference signals that are attributable to CCI and/or AWGN, and those that are attributable to their differing underlying modulating symbols. Conventional correlation demodulators, which simply cross-correlate each received signal with all possible reference signals, are unable to make this distinction, and thus select many incorrect reference signals as estimates of information signals when operating in the mobile radio environment.
Some existing correlation demodulators do try to model the effects of AWGN and CCI by making use of history correlation data. History correlation data is a record of the received signals and information signal estimates that have been previously made by the demodulator. Such demodulators however, are not generally applicable to all digitally modulated signals, these signals being any digital signal that has been modulated using a scheme that recognizes a finite number of symbols. For example, an article entitled "Data-aided Non-coherent Demodulation of DPSK" in IEEE Transactions On Communications, Vol. 43, No. 2/3/4, February/March/April 1995, describes a demodulator that makes use of history correlation data, but only to take into account a random phase shift introduced by the channel. The information this demodulator derives from the history correlation data is only applicable to signals conforming with differential phase shift modulation schemes, and using a one-symbol-per-received-signal format.
A correlation demodulator is thus needed that can make use of history correlation data to more accurately demodulate received signals conforming with any digital modulation scheme.
Such demodulators could be deployed in a wide variety of applications. One such application is in the field of frequency modulated (FM) receivers. Conventional FM receivers perform frequency demodulation before attempting correlation detection on the resulting frequency demodulated signals. This is undesirable because much of the amplitude information in the received signal that is lost during frequency demodulation is useful in performing correlation detection. Furthermore, a long delay is imposed on the receiver as a received signal must proceed through a frequency demodulation as well as a correlation detection process before yielding symbols.
FM transmitters conforming with the Advanced Mobile Phone Service (AMPS) wideband data protocol, frequency modulate streams of bits at a rate of 10 kbps, which each must be over-sampled in light of the wide bandwidth associated with each FM signal. However, the AMPS signal is commonly sampled at 48,600 samples per second in order to conform with the more widely used TDMA protocol. This non-integer over-sampling of the AMPS signals (i.e. 4.86 samples per symbol) is the cause of additional processing requirements at the receiver to interpolate the signal to an integer over-sample ratio.
FM receivers are plagued by inter-symbol interference caused by filter responses in the transmitter and the receiver. These responses will persistently manifest themselves as the overlapping of one received signal into temporally adjacent received signals. It is desired that such responses be factored into the operation of demodulators deployed in FM receivers.